A study on the conversion of prescribed dose for radiotherapy of logistic nanodosimetry model and microdosimetric kinetic model based on gamma analysis
Yang Jingfen1,2, Zhang Hui1,2, Liu Xinguo1,2, Dai Zhongying1,2, He Pengbo1,2, Ma Yuanyuan1,2, Shen Guosheng1,2, Chen Weiqiang1,2, Li Qiang1,2
1Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China; 2University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:Objective To validate the feasibility of the gamma analysis method in the study of prescription dose conversion between logistic nanodosimetry model (LNDM) and microdosimetric kinetic model (MKM) basing on the Chinese self-developed model LNDM by applying clinical experiences of National Institute of Radiological Science (NIRS). Methods Physical dose distributions derived from the MKM- and LNDM-based carbon ion treatment plans were compared via the method of gamma analysis under the open-source treatment planning platform matRad. In this way, the prescribed dose conversion factor between the MKM- and LNDM-based treatment plans was obtained. Using water phantoms, the influence of geometric shape, size, depth of target volume (TV), prescribed dose and field setting on the conversion factor was investigated comprehensively. Moreover, preliminary verification of the acquired conversion factor was conducted on the C-shape model and a case of liver cancer patient. Results The conversion factor depended on the field setting rather than the TV shape. Under the condition of single field, the conversion factor was positively correlated with the size and depth of TV, and the prescribed dose. Moreover, the conversion factor was successfully verified using the C-shape model and the patient with liver cancer, where the gamma passing rates (2%/2 mm) of the physical dose distribution generated by the MKM and LNDM treatment plans were 92.79% and 91.19%, respectively. Conclusions The conversion factors (f=DLNDM/DMKM) obtained in this study might provide guidance for the prescribed dose setting during the carbon ion treatment planning based on the LNDM. Besides, the gamma analysis method could be used for the study of the prescribed dose conversion between different models.
Yang Jingfen,Zhang Hui,Liu Xinguo et al. A study on the conversion of prescribed dose for radiotherapy of logistic nanodosimetry model and microdosimetric kinetic model based on gamma analysis[J]. Chinese Journal of Radiation Oncology, 2023, 32(4): 325-332.
[1] Kraft G. Tumor therapy with heavy charged particles[J]. Progress in Particle and Nuclear Physics, 2000,45(Suppl 2):S473-S544. DOI: 10.1016/S0146-6410(00)00112-5. [2] Kanai T, Endo M, Minohara S, et al.Biophysical characteristics of HIMAC clinical irradiation system for heavy-ion radiation therapy[J]. Int J Radiat Oncol Biol Phys, 1999,44(1):201-210. DOI: 10.1016/s0360-3016(9 8)00544-6. [3] Scholz M, Kellerer AM, Kraft-Weyrather W, et al.Computation of cell survival in heavy ion beams for therapy. The model and its approximation[J]. Radiat Environ Biophys, 1997,36(1):59-66. DOI: 10.1007/s004110050055. [4] Hawkins RB.A microdosimetric-kinetic model of cell death from exposure to ionizing radiation of any LET, with experimental and clinical applications[J]. Int J Radiat Biol, 1996,69(6):739-755. DOI: 10.1080/0955300961 45481. [5] Tsujii H, Mizoe J, Kamada T, et al. Clinical results of carbon ion radiotherapy at NIRS[J]. J Radiat Res, 2007,48 Suppl A:A1-A13. DOI: 10.1269/jrr.48.a1. [6] Yanagi T, Mizoe JE, Hasegawa A, et al.Mucosal malignant melanoma of the head and neck treated by carbon ion radiotherapy[J]. Int J Radiat Oncol Biol Phys, 2009,74(1):15-20. DOI: 10.1016/j.ijrobp.2008.07.056. [7] Okada T, Kamada T, Tsuji H, et al.Carbon ion radiotherapy: clinical experiences at National Institute of Radiological Science (NIRS)[J]. J Radiat Res, 2010,51(4):355-364. DOI: 10.1269/jrr.10016. [8] Mizoe JE, Tsujii H, Kamada T, et al.Dose escalation study of carbon ion radiotherapy for locally advanced head-and-neck cancer[J]. Int J Radiat Oncol Biol Phys, 2004,60(2):358-364. DOI: 10.1016/j.ijrobp.2004.02.067. [9] Kamada T, Tsujii H, Tsuji H, et al.Efficacy and safety of carbon ion radiotherapy in bone and soft tissue sarcomas[J]. J Clin Oncol, 2002,20(22):4466-4471. DOI: 10.1200/JCO.2002.10.050. [10] Ishikawa H, Tsuji H, Kamada T, et al.Carbon-ion radiation therapy for prostate cancer[J]. Int J Urol, 2012,19(4):296-305. DOI: 10.1111/j.1442-2042.2012.02961.x. [11] Imai R, Kamada T, Sugahara S, et al. Carbon ion radiotherapy for sacral chordoma[J]. Br J Radiol, 2011,84 Spec No 1(Spec Iss 1):S48-54. DOI: 10.1259/bjr/1378 3281. [12] Kanai T, Matsufuji N, Miyamoto T, et al.Examination of GyE system for HIMAC carbon therapy[J]. Int J Radiat Oncol Biol Phys, 2006,64(2):650-656. DOI: 10.1016/j.ijrobp.2005.09.043. [13] Dai T, Li Q, Liu X, et al.Nanodosimetric quantities and RBE of a clinically relevant carbon-ion beam[J]. Med Phys, 2020,47(2):772-780. DOI: 10.1002/mp.13914. [14] 曹午飞, 黄晓延, 孙文钊, 等. 剂量分布验证中分辨率对Gamma通过率的影响[J].中华放射肿瘤学杂志,2012,21(2):172-175. DOI: 10.3760/cma.j.issn.1004-4221. 2012.02.023. Cao WF, Huang XY, Sun WZ, et al.The impact of resolution to gamma pass rate in the verification of dose distribution[J].Chin J Radiat Oncol,2012,21(2):172-175. DOI: 10.3760/cma.j.issn.1004-4221.2012.02.023. [15] Jan S, Benoit D, Becheva E, et al.GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy[J]. Phys Med Biol, 2011,56(4):881-901. DOI: 10.1088/0031-9155/56/4/001. [16] Wieser HP, Cisternas E, Wahl N, et al.Development of the open-source dose calculation and optimization toolkit matRad[J]. Med Phys, 2017,44(6):2556-2568. DOI:10.1002/mp.12251. [17] Craft D, Bangert M, Long T, et al.Shared data for intensity modulated radiation therapy (IMRT) optimization research: the CORT dataset[J]. Gigascience, 2014,3(1):37. DOI: 10.1186/2047-217X-3-37. [18] Cisternas E, Mairani A, Ziegenhein P, et al.matRad - a multi-modality open source 3D treatment planning toolkit[M]//Jaffray DA. World Congress on Medical Physics and Biomedical Engineering. New York: Spring, 2015:1608-1611. [19] 戴天缘, 李强, 陈卫强, 等. 基于微剂量学蒙特卡罗模拟的重离子生物有效剂量精确计算方法[J].中国医学物理学杂志,2019,36(10):1119-1124. DOI: 10.3969/j.issn.1005- 202X.2019.10.001. Dai TY, Li Q, Chen WQ, et al.An accurate method for calculating biological effective doses of therapeutic heavy ions based on microdosimetric Monte Carlo simulation[J].Chinese Journal of Medical Physics,2019,36(10):1119-1124. DOI: 10.3969/j.issn.1005-202X.2019.10.001.